How to start capitalizing on IoT

The potential of IoT and IIoT solutions to transform industries is undeniable, offering businesses unprecedented opportunities to reduce costs, boost efficiency, and generate  new revenue streams. However, realizing these benefits requires careful planning and strategic execution. Without a structured approach, even the most promising projects can face unexpected challenges, leading to wasted resources and missed opportunities.

Getting started with IoT means more than adding sensors or connecting devices. It’s about creating a well-integrated ecosystem that aligns with your business objectives, employs the right technologies, and manages potential risks.

Here’s a step-by-step guide to setting your IoT projects on the path to success.

Step 1. Consulting with experts

According to a Cisco survey, over 60% of respondents admitted that they underestimated the complexities of building their own IoT services, while 75% of self-initiated IoT projects were considered failures.

Some risks aren’t apparent at first and can only be identified by those with industry expertise. Imagine a system with thousands of devices spread across various locations — perhaps across different parts of a city or even across cities — transmitting data to a central domain. If an urgent need arises to change the domain or a critical bug is discovered in the device firmware, the situation could escalate quickly. Without over-the-air (OTA) update capabilities, the organization might need to send personnel to physically update each device — resulting in significant, avoidable costs.

Experienced IoT specialists can help identify these hidden risks early on and guide you in selecting the right technologies. They provide valuable advice on hardware and the technological stack, tailored to your budget and goals. By consulting with experts, you can ensure a solid foundation for your IoT project, reducing the likelihood of costly setbacks and maximizing your chances of success.

Step 2. Setting business goals

Imagine a world where all the objects around you are smart and connected to the Internet — even those you might not think could ever be connected. While you may already know the business problem you want to solve, this concept encourages you to think beyond the obvious and explore new ways to address it.

At this stage, take time to reflect on your business's growth opportunities and align them with your problem-solving strategy. Clearly define what you aim to achieve and how IoT can help you get there. Start with a focused, manageable goal rather than an overly complex one. IoT implementation can be incremental, aligned with the budget you’re able to allocate each month.

Example:

Let’s say your goal is to enhance elderly care. The specific problem you want to address is detecting falls and determining whether immediate assistance is required. You have several options to achieve this, such as a wearable device equipped with sensors (like an Apple Watch) to detect falls, or a video monitoring solution with deep learning capabilities that identifies falls almost in real time. By defining your goal and exploring available methods, you can design a solution that aligns with your needs and resources while paving the way for future scalability.

Step 3. Choosing an implementation model

Once you’ve identified your problem and defined your goals, the next step is to explore whether your solution aligns with common implementation models. Opting for a well-established business model can be a smart move, as these approaches have already proven successful across various industries.

However, your unique business processes may require — and often will require — customizing the chosen model to fit your specific needs. This is why we recommend conducting a thorough analysis of your processes at this stage. Collaborating with experts can help you ensure that the implementation model is tailored to achieve optimal results for your business.

Step 4. Choosing hardware

What will be connected to your IoT system? There are countless possibilities for connected devices across any industry. The project’s cost and overall effectiveness heavily depend on these choices, as the right hardware is critical to ensuring the system’s operability. Selecting the appropriate devices is no simple task, requiring careful consideration of factors like energy consumption, connectivity, performance, and cost — all of which influence the network’s functionality and budget.

Here are some examples of what can be integrated into your IoT network:

Step 5. Selecting your platform

An IoT platform is the backbone of an IoT network, serving as the software hub that manages and centralizes all aspects of the connected devices and systems. These platforms collect data, typically through public or private cloud integrations, and facilitate communication between devices and other systems. Choosing the right platform is essential for scalability and adaptability, ensuring your IoT solution meets current needs while staying flexible for future growth.

Some popular IoT platforms include:

• PTC ThingWorx

• Tarantool IoT Platform

• SAP BPT

• Siemens Mindsphere

• Azure IoT Platform

• ThingsBoard

In certain cases, building a custom IoT platform from scratch can be a viable option if it’s economically reasonable. Such platforms can significantly accelerate solution development by enabling highly specific features, such as tailored data processing workflows and personalized user interfaces

Sergey Ponomarenko

Head of IoT practice at WaveAccess

The platform you choose plays a critical role in how devices exchange data and how that data is processed. While switching platforms later is technically possible, it often requires extensive code revisions, making it a costly and time-consuming endeavor.

Many platforms, however, offer flexibility through plugins and extensions, allowing businesses to enhance and expand their solutions without starting from scratch. Additionally, these platforms often come with robust integration features, making it easier to connect with existing systems and other technologies.

Step 6. Prototyping and design

The prototyping stage marks the transformation of your idea into a tangible Proof of Concept (PoC). At this stage, budgets are often limited, and deadlines can be tight, especially if the goal is to secure funding or make decisions about the project’s future.

A well-designed, functional prototype can be developed quickly, even without detailed formal specifications. The key is to define your goals clearly, leverage expert knowledge, and test your concept with a PoC to evaluate its feasibility and potential.

By focusing on rapid development and iterative testing, you can refine your idea and demonstrate its value.

Step 7. System integration

IoT enables data collection from a wide range of devices, but integrating these devices into a cohesive system is often a complex challenge. Many devices are not inherently compatible with other systems, and their sensors generate data in varying formats. This is where middleware plays a crucial role, acting as a bridge to connect devices with external systems such as databases or corporate software.

Data integration and the analytics that rely on it are among the biggest hurdles in IoT development. Middleware solutions and gateways help address these challenges by standardizing data exchange and enabling seamless communication. There are numerous gateways available, each offering unique features, including:

• Fanuc

• Allen Bradley

• Siemens SIMATIC

• CloudGate

• Libelium Meshlium

• Multitech

Additionally, certain products, such as Keepware Server, decode signals from devices using diverse protocols and unifying information exchange.

Selecting the right tools for system integration ensures that your IoT network functions efficiently and supports the analytics needed for actionable insights.

Step 8. Data analysis

In IoT, we always work with time-bound data that is stored in time-series databases. This data, ingested from sensors and devices, can be analyzed to extract knowledge and represent it in various formats to support informed decision-making.

While the majority (up to 90%) of IoT data visualizations are time-based charts, with the X-axis representing time, data analysis extends far beyond simple graphs. For instance, you may need to display the real-time status of an object and its parameters; aggregate data for summaries and trend analysis; manage and monitor objects on geographical maps or mnemonic diagrams. Mature IoT platforms provide tools for creating dashboards, customizing visualizations, and tailoring data views to specific needs.